Luis Rodrigo Barba Guamán
Biography. I received an MSc. from Polytechnic of Madrid in 2015, working at the use of artificial vision methods for PC as support in the automotive industry with José Naranjo. My MSc thesis explored the edges and lines on the road, moreover object detection which will help to inform or prevent the driver or computer system from running over the objects through an alert. Till April 2008, I was a technology and education area in "Modalidad Abierta y a Distancia " from the Technical University of Loja, Ecuador. We develop software to support education such as remote work automation and video conference systems. I was leading the technical area in the Global Development Learning Network team for Latin America. in 2010. I joined the Computer Science and Electronics Department at the Technical University of Loja in 2014.
Research. My research explores image processing and computer vision algorithms on the road through traditional and deep learning techniques. More broadly, my research interests encompass serious game development.
Design, analysis, and clustering of data with ant colony techniques. experiments in the sorting and grouping characteristics. Design a serious game MateBRU as a strategy to teach basic arithmetic operations for six-years-old children
Using of neural networks for the detection, classification and automated counting of vehicles and pedestrians in public space.
I have collaborated and leading in for 27 research, development, and innovation major projects
Areas of technical interest include mathematics learning, intelligence systems, and computer vision.
Funding. My work has been supported by an Ecuadorian Corporation for the Development of Research and Academia, CEDIA, for the financing provided to research, through the especially the CEPRA project - XII -2018; The name of the project is "Clasificadorvideo para actores de la movilidad como alternativa a conteos volumétricos manuales" and the research project call from Technical University of Loja.
Address: Loja, Ecuador
Research. My research explores image processing and computer vision algorithms on the road through traditional and deep learning techniques. More broadly, my research interests encompass serious game development.
Design, analysis, and clustering of data with ant colony techniques. experiments in the sorting and grouping characteristics. Design a serious game MateBRU as a strategy to teach basic arithmetic operations for six-years-old children
Using of neural networks for the detection, classification and automated counting of vehicles and pedestrians in public space.
I have collaborated and leading in for 27 research, development, and innovation major projects
Areas of technical interest include mathematics learning, intelligence systems, and computer vision.
Funding. My work has been supported by an Ecuadorian Corporation for the Development of Research and Academia, CEDIA, for the financing provided to research, through the especially the CEPRA project - XII -2018; The name of the project is "Clasificadorvideo para actores de la movilidad como alternativa a conteos volumétricos manuales" and the research project call from Technical University of Loja.
Address: Loja, Ecuador
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Papers by Luis Rodrigo Barba Guamán
importante en los sistemas inteligentes de transportación, así como la
detección de objetos tal como vehículos, con la finalidad de informar o prevenir
a través de una alerta al conductor o al sistema informático.
De aquí nace el interés de analizar algunos métodos de visión artificial (VA)
que es un subcampo de la inteligencia artificial, cuyo propósito es programar un
computador y que este “entienda” una escena o imagen, algunos de los
métodos más comunes en la detección de líneas y vehículos (considerados
objetos en nuestra investigación) son la transformada de Hough, el método de
Canny, clasificador Haar Cascade, filtros de Fourier, etc. Se desarrollará una
aplicación de escritorio o PC (Personal Computer) para el reconocimiento de
vehículos y las líneas de bordes, el lenguaje de programación utilizado será
Python y la biblioteca OpenCV que contiene más de 500 funciones en el campo
de visión por computador
La validación del reconocimiento de objetos se la realizará con una prueba de
campo. Este resultado apoyará a la automoción (máquina que se desplaza por
acción de un motor como el vehículo) con datos que luego pueden ser
procesados.